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Aalto University is a newly created university from the merger of three Finnish universities: Helsinki School of Economics, University of Art and Design Helsinki, and Helsinki University of Technology – all leading and renowned institutions in their respective fields and in their own right. Aalto University will contribute with the expertise and international recognition of the Department of Biomedical Engineering and Computational Science (BECS) and the Department of Information and Computer Science (ICS).

BECS is an interdisciplinary research environment, and has hosted the Academy of Finland Center of Excellence of Computational Complex Systems Research (COSY), in the period 2000-2011. The research conducted at BECS focuses on living and other complex systems, their measurement, analysis, modelling, understanding and control. The scale of the systems of interest ranges from quantum dots to broad networks: nanosystems, molecular interactions, neurons, the brain and the heart, cognition, information technology systems and social and economic networks. BECS combines experimental and computational methods and develops algorithms and new technologies to tackle major problems in human well-being, medical diagnostics, energy, the society and the environment.

The department of ICS focuses on research on advanced computational methods for modelling, analyzing, and solving complex tasks in technology and science. The research aims at the development of fundamental computer science methods for the analysis of large and high-dimensional datasets, and for the modelling and design of complex software, networking and other computational systems. Currently, the department hosts three national Centres of Excellence (COIN, SyMMyS, and ReSoLVE). The department also contributes to the Helsinki Institute for Information Technology HIIT and the Helsinki node of the EIT ICT Labs. The department is a member of Informatics Europe, the association of European computer science departments. The department of ICS has long-standing tradition in the areas of machine learning and data mining, and it attracts a continuous stream of bright Ph.D students and postdoctoral researchers from Finland and abroad. 


Role in the Project

AALTO are providing transnational access methods to a social network analysis infrastructure for analyzing and extracting knowledge from large social network datasets. AALTO are also leading WP3 on dissemination, impact, and community building. In particular, they lead T3.5 on community building. In the JRAs in WP9, AALTO will lead T9.1, which will develop and integrate methods for exploration of social ego-networks, information flow on the networks, opinion dynamics in social networks, analysis of dynamic interaction networks, team formation in social networks.